Linking understanding and usage of Automated Driver Assistance Systems (ADAS)

What is it about?

Automated Driver Assistance Systems (ADAS), which aim to enhance safety and comfort while driving, are becoming increasingly popular in vehicles today. However, ADAS are not yet operative in every situation due to technical limitations, and therefore do not cover all driving situations, traffic, weather and/or road conditions. In order for drivers to use these systems in a safe manner, they need to understand the different modes of operation, as well as the limitations of the systems, or they will not be able to build appropriate trust and adequate usage strategies. Therefore, the purpose of this study was to investigate the factors influencing user understanding of ADAS by implementing an Explanatory Sequential Mixed Methods design. This was done by triangulating data from a Naturalistic Driving (ND) study (132 vehicles) with explanations and reflections from in-depth interviews of purposefully selected participants (12 drivers from the vehicle pool) who were showing different usage patterns. The results show that users’ understanding is influenced by preconceptions about the system, as well as the perceived system performance and usefulness, leading to different levels of trust that affect the users’ engagement with the ADAS. It was found that the driver’s perception of a system does not just change over time, but changes through different situations presented, challenging the expected events and the users’ mental model of the interaction with the system. Therefore, to gain trust and appropriate usage strategies for the ADAS the user needs to overcome potentially negative experiences and challenge the current understanding of the ADAS, by stepping over the threshold.

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Why is it important?

•Usage of ADAS is influenced by users pre-conceptions and perceived usefulness of the systems •Trust and acceptance are especially affected by the perceived system performance. •Users build situational trust into the system, which is connected to the context of use. •For the user to understand the system capabilities and limitations, the learning experiences need to challenge the users’ mental model of the interaction with the system.